Guillermo Lorenzo


Patient-specific, imaging-based forecasting of prostate cancer growth

This research aims at integrating standard clinical and imaging data from individual patients into mathematical models to enable the prediction of tumor growth using computer simulations

Personalized prediction of PSA dynamics after external radiotherapy of prostate cancer

Exploring the biophysical mechanisms underlying PSA dynamics after external radiotherapy to define new biomarkers for the early identification of relapse

Optimal control of therapeutic regimens for advanced prostate cancer

This work aims at finding optimal combinations of cytotoxic and antiangiogenic therapies to treat advanced prostatic tumors by combining mathematical analysis and computer simulations

Integrating multiscale data and mechanistic models to predict breast cancer response to neoadjuvant therapies

Personalized prediction of breast cancer response to neoadjuvant therapies by using biophysical models parameterized with patient-specific imaging data and constrained by comprehensive pharmacodynamic experimental data

Data-driven mechanistic models to forecast COVID-19 outbreaks

Constructing mathematical models to understand and predict the dynamics of COVID-19 infectious spread based on longitudinal epidemiological data series